代码如下: print("转换结果:",text) 1. 4. 示例代码 importspeech_recognitionassr# 创建 Recognizer 对象r=sr.Recognizer()# 从音频文件中读取音频audio_file="audio.wav"withsr.AudioFile(audio_file)assource:audio=r.record(source)# 使用 Recognizer 对象进行语音转文本text=r.recognize_google(audio)# 输出...
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cosyvoice = CosyVoice2('pretrained_models/CosyVoice2-0.5B', load_jit=True, load_onnx=False, load_trt=False) # NOTE if you want to reproduce the results on https://funaudiollm.github.io/cosyvoice2, please add text_frontend=False during inference # zero_shot usage prompt_speech_16k = ...
language:语言代码,model:模型,response_format:text|json|srt # 返回 code==0 成功,其他失败,msg==成功为ok,其他失败原因,data=识别后返回文字 files = {"file": open("C:/Users/c1/Videos/2.wav", "rb")} data={"language":"zh","model":"base","response_format":"json"} response = requests...
Multilingual Voice Understanding Model. Contribute to FunAudioLLM/SenseVoice development by creating an account on GitHub.
<datasets_root>替换为你的数据集目录,<synthesizer_model_path>替换为一个你最好的synthesizer模型目录,例如sythensizer\saved_mode\xxx 训练wavernn声码器:python vocoder_train.py <trainid> <datasets_root> <trainid>替换为你想要的标识,同一标识再次训练时会延续原模型 ...
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语音合成,又称文本转语音(Text-to-Speech,TTS),是将文本转换为自然语音的技术。该技术基于机器学习算法,通过学习大量语音样本,掌握语言的韵律、语调和发音规则,从而在接收到文本输入时生成真人般自然的语音内容。 示例场景和语音 聊天数字人 日常闲聊 cosyvoice-v1(longxiaochun):这这也不知道为啥哈,反正,它刚出来...
To set finer-grained speed levels, keep one decimal place, such as 0.5, 1.1, and 1.8. ProjectIdNoIntegerProject ID, which defaults to 0 and can be customized. ModelTypeNoIntegerModel type, with1for the default model. VoiceTypeNoIntegerStandard voices ...
Python 3.7 is recommended. Python 3.5 or greater should work, but you'll probably have to tweak the dependencies' versions. I recommend setting up a virtual environment usingvenv, but this is optional. Installffmpeg. This is necessary for reading audio files. ...